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Minerva: a fast and flexible tool for deep learning. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy. Please refer to the examples to see how multi-GPU setting is used.

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Minerva: a fast and flexible system for deep learning

Minerva is a fast and flexible tool for deep learning. It provides NDarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy. Please refer to the examples to see how multi-GPU setting is used.Minerva is a fast and flexible tool for deep learning. It provides NDarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy. Please refer to the examples to see how multi-GPU setting is used.

Features

  • Matrix programming interface
  • Easy interaction with NumPy
  • Multi-GPU, multi-CPU support
  • Good performance: ImageNet AlexNet training achieves 213 and 403 images/s with one and two Titan GPU, respectivly. Four GPU cards number will be coming soon.

License and support

Minerva is provided in the Apache V2 open source license.

You can use the "issues" tab in github to report bugs. For non-bug issues, please send up an email at [email protected].

Wiki

For more information on how to install, use or contribute to Minerva, please visit our wiki page: https://github.com/minerva-developers/minerva/wiki

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Minerva: a fast and flexible tool for deep learning. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy. Please refer to the examples to see how multi-GPU setting is used.

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  • C++ 52.2%
  • Python 36.1%
  • Cuda 5.7%
  • Protocol Buffer 5.2%
  • Other 0.8%